- This is the implementation used in [Zero-Shot Relation Extraction via Reading Comprehension][paper1] (Levy et al., 2017).
- It is an extension of the [BiDAF model][paper2] by Seo et al.
- This file describes some basic use-cases in the relation-extraction setting. The original implementation's readme file is [BiDAF_README.md][fullreadme].
- Python (developed on 3.5.2. Issues have been reported with Python 2!)
- tensorflow (deep learning library, verified on r0.11)
- nltk (NLP tools, verified on 3.2.1)
- tqdm (progress bar, verified on 4.7.4)
run_prep.sh <run name>calls an internal script (zeroshot2squad.py) that changes our tab-delimited format to SQuAD's JSON format. It then performs any necessary preprocessing for the BiDAF model.run_train.sh <run name>runs the training procedure.run_test.sh <run name>runs the testing procedure, and yields an answer file inout/basic/<run name>/test-#####.jsonpython analyze.py <test set> <answer file>reads the test set and the model's answers, and returns the F1 score broken down by different factors.
[paper1]: [paper2]: https://arxiv.org/abs/1611.01603 [fullreadme]: BiDAF_README.md